In graphics processing, light transport simulation is utilized to generate graphical images in which light is being transported for example via specular or refractive surfaces. For example, such light transport may include light entering a car through a window, hitting the interior, and being transported back through the window to an outside observer, or the observation of a room through a mirror, where substantial illumination of the room is due to a small light source through the mirror.
In principle, light transport simulations sum up the contributions of all transport paths, which connect light sources with sensors. Traditionally, techniques providing numerical simulation have included bidirectional path tracing algorithms, where random walk methods are used to generate paths from the sensors and lights in order to connect them. However, there are common situations where establishing such connections by checking visibility using shadow rays can be arbitrarily inefficient. For example, in the context of bidirectional path tracing this problem has been characterized as the problem of “insufficient techniques” (see Efficient bidirectional path tracing by randomized quasi-Monte Carlo integration, by T. Kollig and A. Keller, Monte Carlo and Quasi-Monte Carlo Methods 2000 [H. Niederreiter, K. Fang, and F. Hickernell, eds.], Springer, 2002, pp. 290-305), in which unbiased Monte Carlo algorithms are unable to handle light transport due to specular surfaces in an efficient manner. To somebody skilled in the art, it is known, that deterministic methods can outperform randomized and/or unbiased algorithms with respect to the speed of convergence. In addition deterministic methods can be easily parallelized. However, such deterministic methods do not exist in the prior art of light transport simulation, where the problem of insufficient techniques is encountered.
There is thus a need for addressing these and/or other issues associated with the prior art.